Zobrazeno 1 - 10
of 11
pro vyhledávání: '"39"'
Autor:
Alderson TH; Intelligent Systems Research Centre, Ulster University, UK. Electronic address: thomashenryalderson@gmail.com., Bokde ALW; Trinity College Institute of Neuroscience and Cognitive Systems Group, Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Ireland., Kelso JAS; Intelligent Systems Research Centre, Ulster University, UK; Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, USA., Maguire L; Intelligent Systems Research Centre, Ulster University, UK., Coyle D; Intelligent Systems Research Centre, Ulster University, UK.
Publikováno v:
NeuroImage [Neuroimage] 2018 Dec; Vol. 183, pp. 438-455. Date of Electronic Publication: 2018 Aug 18.
Autor:
Park G; Department of Biomedical Engineering, Hanyang University, Seoul, South Korea., Hong J; Department of Biomedical Engineering, Hanyang University, Seoul, South Korea., Duffy BA; USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA., Lee JM; Department of Biomedical Engineering, Hanyang University, Seoul, South Korea. Electronic address: ljm@hanyang.ac.kr., Kim H; USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90033, USA.
Publikováno v:
NeuroImage [Neuroimage] 2021 Aug 15; Vol. 237, pp. 118140. Date of Electronic Publication: 2021 May 03.
Autor:
Challis E; Department of Physics and Astronomy, University of Sussex, Falmer, East Sussex BN1 9QH, UK., Hurley P; Department of Physics and Astronomy, University of Sussex, Falmer, East Sussex BN1 9QH, UK., Serra L; Neuroimaging Laboratory, Santa Lucia Foundation, Via Ardeatina 306, Roma, Italy., Bozzali M; Neuroimaging Laboratory, Santa Lucia Foundation, Via Ardeatina 306, Roma, Italy., Oliver S; Department of Physics and Astronomy, University of Sussex, Falmer, East Sussex BN1 9QH, UK., Cercignani M; Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, University of Sussex, Falmer, East Sussex BN1 9PR, UK. Electronic address: m.cercignani@bsms.ac.uk.
Publikováno v:
NeuroImage [Neuroimage] 2015 May 15; Vol. 112, pp. 232-243. Date of Electronic Publication: 2015 Feb 28.
Autor:
Hua X; Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Neuroscience Research Building 225E, 635 Charles Young Drive, Los Angeles, CA 90095-1769, USA., Lee S, Hibar DP, Yanovsky I, Leow AD, Toga AW, Jack CR Jr, Bernstein MA, Reiman EM, Harvey DJ, Kornak J, Schuff N, Alexander GE, Weiner MW, Thompson PM
Publikováno v:
NeuroImage [Neuroimage] 2010 May 15; Vol. 51 (1), pp. 63-75. Date of Electronic Publication: 2010 Feb 06.
Autor:
Filippini N; The Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford, Oxford, UK., Rao A, Wetten S, Gibson RA, Borrie M, Guzman D, Kertesz A, Loy-English I, Williams J, Nichols T, Whitcher B, Matthews PM
Publikováno v:
NeuroImage [Neuroimage] 2009 Feb 01; Vol. 44 (3), pp. 724-8. Date of Electronic Publication: 2008 Nov 01.
Publikováno v:
NeuroImage, Vol 237, Iss, Pp 118140-(2021)
NeuroImage
NeuroImage
White matter hyperintensities (WMHs) are abnormal signals within the white matter region on the human brain MRI and have been associated with aging processes, cognitive decline, and dementia. In the current study, we proposed a U-Net with multi-scale
Autor:
Alex D. Leow, Arthur W. Toga, Paul M. Thompson, Priya Rajagopalan, Derrek P. Hibar, Christopher R.K. Ching, Clifford R. Jack, Christina P. Boyle, Danielle J Harvey, Xue Hua, Boris A. Gutman, Michael W. Weiner
Publikováno v:
NeuroImage. 66:648-661
Various neuroimaging measures are being evaluated for tracking Alzheimer's disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Met
Autor:
Cynthia M. Stonnington, Stefan Klöppel, Richard S.J. Frackowiak, John Ashburner, Clifford R. Jack, Carlton Chu
Publikováno v:
NeuroImage
NeuroImage, vol. 51, no. 4, pp. 1405-1413
NeuroImage, vol. 51, no. 4, pp. 1405-1413
Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scan
Autor:
Inge Loy-English, Paul M. Matthews, Danilo Guzman, Rachel A. Gibson, Nicola Filippini, Anil Rao, Andrew Kertesz, Sally Wetten, Brandon Whitcher, Julie Williams, Thomas E. Nichols, Michael Borrie
Publikováno v:
NeuroImage. 44:724-728
APOE epsilon4 is the best-established genetic risk factor for sporadic Alzheimer's disease (AD). However, while homozygotes show greater disease susceptibility and earlier age of onset than heterozygotes, they may not show faster rates of clinical pr
Publikováno v:
NeuroImage. 25:320-327
We examined the relationship between structural brain variation and general intelligence using voxel-based morphometric analysis of MRI data in men and women with equivalent IQ scores. Compared to men, women show more white matter and fewer gray matt